Update app.py

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 import torch
+import cv2
 import time
 from PIL import Image
 # Images
@@ -7,6 +8,9 @@ torch.hub.download_url_to_file('https://cdn.pixabay.com/photo/2016/06/15/01/11/s
 torch.hub.download_url_to_file('https://cdn.pixabay.com/photo/2016/11/21/14/31/vw-bus-1845719_1280.jpg', 'bus.jpg')
 # Model
 model = torch.hub.load('ultralytics/yolov3', 'yolov3')  # or yolov3-spp, yolov3-tiny, custom
+
+cam = cv2.VideoCapture(0)
+
 def yolo(im, size=640):
     g = (size / max(im.size))  # gain
     im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS)  # resize
@@ -14,13 +18,14 @@ def yolo(im, size=640):
     results.render()  # updates results.imgs with boxes and labels
     return Image.fromarray(results.imgs[0])
 #inputs = gr.inputs.Image(type='pil', label="Original Image")
+title = "Определение элементов"
+description = "Находит на картинке элементы"
+article = "тест"
+examples = [['soccer.jpg'], ['bus.jpg']]
+
 while True:
-    inputs=gr.inputs.Image(type="pil",source="webcam")
+    #inputs=gr.inputs.Image(type="pil",source="webcam")
     outputs = gr.outputs.Image(type="pil", label="Output Image")
-    title = "Определение элементов"
-    description = "Находит на картинке элементы"
-    article = "тест"
-    examples = [['soccer.jpg'], ['bus.jpg']]
-    gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples, theme="huggingface").launch(
-        debug=True)
-    time.sleep(1)
+    ret, frame = cam.read()
+    inputs = Image.fromarray(frame)
+    gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples, theme="huggingface").launch(debug=True)